The Boost.Asio library offers side-by-side support for synchronous and
asynchronous operations. The asynchronous support is based on the Proactor
design pattern [POSA2].
The advantages and disadvantages of this approach, when compared to a synchronous-only
or Reactor approach, are outlined below.

Let us examine how the Proactor design pattern is implemented in Boost.Asio,
without reference to platform-specific details.

Proactor design pattern (adapted from [POSA2])

— Asynchronous Operation

Defines an operation that is executed asynchronously, such as an asynchronous
read or write on a socket.

— Asynchronous Operation Processor

Executes asynchronous operations and queues events on a completion event
queue when operations complete. From a high-level point of view, services
like stream_socket_service
are asynchronous operation processors.

— Completion Event Queue

Buffers completion events until they are dequeued by an asynchronous
event demultiplexer.

— Completion Handler

Processes the result of an asynchronous operation. These are function
objects, often created using boost::bind.

— Asynchronous Event Demultiplexer

Blocks waiting for events to occur on the completion event queue, and
returns a completed event to its caller.

— Proactor

Calls the asynchronous event demultiplexer to dequeue events, and dispatches
the completion handler (i.e. invokes the function object) associated
with the event. This abstraction is represented by the io_service class.

— Initiator

Application-specific code that starts asynchronous operations. The initiator
interacts with an asynchronous operation processor via a high-level interface
such as basic_stream_socket,
which in turn delegates to a service like stream_socket_service.

On many platforms, Boost.Asio implements the Proactor design pattern in
terms of a Reactor, such as select,
epoll or kqueue. This implementation approach
corresponds to the Proactor design pattern as follows:

— Asynchronous Operation Processor

A reactor implemented using select,
epoll or kqueue. When the reactor indicates
that the resource is ready to perform the operation, the processor executes
the asynchronous operation and enqueues the associated completion handler
on the completion event queue.

— Completion Event Queue

A linked list of completion handlers (i.e. function objects).

— Asynchronous Event Demultiplexer

This is implemented by waiting on an event or condition variable until
a completion handler is available in the completion event queue.

On Windows NT, 2000 and XP, Boost.Asio takes advantage of overlapped I/O
to provide an efficient implementation of the Proactor design pattern.
This implementation approach corresponds to the Proactor design pattern
as follows:

— Asynchronous Operation Processor

This is implemented by the operating system. Operations are initiated
by calling an overlapped function such as AcceptEx.

— Completion Event Queue

This is implemented by the operating system, and is associated with an
I/O completion port. There is one I/O completion port for each io_service instance.

— Asynchronous Event Demultiplexer

Called by Boost.Asio to dequeue events and their associated completion
handlers.

Many operating systems offer a native asynchronous I/O API (such as overlapped
I/O on Windows) as the preferred option for developing
high performance network applications. The library may be implemented
in terms of native asynchronous I/O. However, if native support is not
available, the library may also be implemented using synchronous event
demultiplexors that typify the Reactor pattern, such as POSIXselect().

— Decoupling threading from concurrency.

Long-duration operations are performed asynchronously by the implementation
on behalf of the application. Consequently applications do not need to
spawn many threads in order to increase concurrency.

— Performance and scalability.

Implementation strategies such as thread-per-connection (which a synchronous-only
approach would require) can degrade system performance, due to increased
context switching, synchronisation and data movement among CPUs. With
asynchronous operations it is possible to avoid the cost of context switching
by minimising the number of operating system threads — typically a limited
resource — and only activating the logical threads of control that have
events to process.

— Simplified application synchronisation.

Asynchronous operation completion handlers can be written as though they
exist in a single-threaded environment, and so application logic can
be developed with little or no concern for synchronisation issues.

— Function composition.

Function composition refers to the implementation of functions to provide
a higher-level operation, such as sending a message in a particular format.
Each function is implemented in terms of multiple calls to lower-level
read or write operations.

For example, consider a protocol where each message consists of a fixed-length
header followed by a variable length body, where the length of the body
is specified in the header. A hypothetical read_message operation could
be implemented using two lower-level reads, the first to receive the
header and, once the length is known, the second to receive the body.

To compose functions in an asynchronous model, asynchronous operations
can be chained together. That is, a completion handler for one operation
can initiate the next. Starting the first call in the chain can be encapsulated
so that the caller need not be aware that the higher-level operation
is implemented as a chain of asynchronous operations.

The ability to compose new operations in this way simplifies the development
of higher levels of abstraction above a networking library, such as functions
to support a specific protocol.

It is more difficult to develop applications using asynchronous mechanisms
due to the separation in time and space between operation initiation
and completion. Applications may also be harder to debug due to the inverted
flow of control.

— Memory usage.

Buffer space must be committed for the duration of a read or write operation,
which may continue indefinitely, and a separate buffer is required for
each concurrent operation. The Reactor pattern, on the other hand, does
not require buffer space until a socket is ready for reading or writing.